As line search strategy, two methods are used: the first is a simple one based on a parametric function; the second is a normal line search method with Wolfe conditions.
In this paper we expand on our previous work of [ 15] where we introduced a shape-based approach based on a parametric level (PaLS) formulation for the image recovery.
This paper presents an efficient semi-parametric method of identifying regression models based on a parametric copula-based joint probability distribution of input and output variables.
The method presented in this work is based on a parametric function, which offers a number of benefits: Parametric models allow for a faster evolution that is less prone to getting stuck in local minima as the energy is minimised directly by manipulating a few parameters rather than the entire contour.
The first one is related to a mechanical part model (roofing tile) and based on a parametric approach.
This paper contains a proposal based on a parametric study.
An optimal porosity distribution was found based on a parametric study.
Then, a new simple method is developed based on a parametric study using both approaches.
The relevant VLSI design is based on a parametric, highly flexible VHDL description created using a design-reuse approach.
Previous study focused on both a design approach, based on a parametric analysis, and a non-predictive control strategy.
Thus simple design optimization was conducted based on a parametric study on first wall dimensions to improve the design.
